I was literally consfused in gaining the clarity untill you came to the point where you transposed this theory into understanding through tables and the reference with SQL queries, thanks a lot to your efforts for this loving beautiful explaination Arpit sir
Excellent video Arpit . Coming from no software and system engineering background , this was the best video to explain data sharding and partioning . I am a Tech PM for AWS Supply Chain and data partitioning and sharding is real deal for us. Thank for making this extremely easy to understand video
Wow...really nice. Nowadays a lot of people are selling and talking about system design and always try to build some optimistic solution straight forward without going into the internals and in fact they have not even worked on a lot of systems. I strongly feel the way of your explanation is very very nice and I am going to buy your system design plan to improve mine.
2 Important points which i felt could be discussed more are 1) When you said the choice of partitioning depends on the load , usecase and access patterns , can you please give an example of each case ?? 2) When you were talking about the advantages and disadvantages of sharding , have you written these points considering only sharding and no partitioning or have you written considering both sharding and partitioning ??
I am just stunned how you describe every concept that easily and even if the concept is so complicated. I love you and your works man please continue doing it. I promise I will join as a member to this channel as soon as I become an earning developer. :D
This is excellent, high-quality content! I always had questions about sharding and partitioning, but now I understand: sharding pertains to the database server level, while partitioning is about organizing the data itself.
I looove this kind of explanation. i.e stepping back and discussing the scenarios behind why something came up to be. Thanks a lot for these videos man!
Very good explanation with right examples. Hats off to you. Thanks for great content. I always thought shard and partitions are same but you clarified it very well.
This is such a great and simple explanation of partitioning and sharding of a database. Would love to watch the video on partitioning strategies when it is uploaded.
Thanks a lot Arpit for explaining in so simplistic way. One request can you please make video on Sharding strategies and also on how composite indexes stores in the disk.
@asli engineering - Bhai, any update on the sharding strategies. Also, one more request is examples of scenarios to explain shard key selection. How is the data replicated behind the scenes n stuff please ?
Partitioning can be done at table as well. So let's consider we have a table named X and it is having huge data so if we want to increase the performance and improve the latency we can partition the table into Y shards.
Great video ! Nicely explained. :) But I have one query , towards the end of the video : The example you shared for "Sharding NO and partitioning YES" about Airline Check-in System and Ticket Booking System. How is that classified as partitioning if the databases are altogether different ? Any thoughts ?
Great video as always! 👍 I’ve got a question: 🤨 I have these words 🤨. (behave today finger ski upon boy assault summer exhaust beauty stereo over). What should I do with this? 🤷♂️
@arpit Thanks for such dense information in so short and simple video. However I have a query on a corner case - How can have replicas when one has multiple shards with partitioning? - In this case is replication locally on the shard or it can also be replicated on other shards for high availability across avalability zone or DR (like kafka architecture)?
One question, at 21.00 the matrix shows what it looks like when we have both sharding and partioning, how that is different from having two databases on two different EC2 instance for two applications?
Hello arpit, at 5:49, why you mentioned that the new resources are being allocated to the EC2 machine? I think that should be allocated to the DB server running on EC2 machine right?
Great content, as always! I need some advice: My OKX wallet holds some USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). How can I transfer them to Binance?
Hey great video Ankit! I was wondering how sorting and specially filtering would work across shards? Or is that an anti pattern ( just like cross shard joins )
Partitioning allows your database to read/access/move the required subset of data easily and efficiently. 1. Imagine if you partition data by time and create one partition for every hour and someone queries how many events happened in the last 10 hours, you would just need to access last 10 partition to fulfil this query. Others are not even required to be read. 2. In a distributed setup, instead of moving individual rows/elements we can easily and efficiently move partitions across the cluster for balancing the load.
I have a doubt sir. I think increase in overall storage capacity and higher availability, doesn't got hand in hand. If we shard and partition data, then the capacity will be available but then the data is not same in both shards i.e., if one shard becomes offline then the other shard cannot provide data if the requested data is in the offline shard. So no higher availability. And if we only do sharding then the same data will be in both servers, and as u said if we assume 100tb, then the other will also have 100tb only? We cant get 200tb. This is what I thought. Correct me if im wrong.
I too got the same doubt, I came to know that in this case, our system will be available but the data might be inconsistent, so still the server accepts requests and provides an empty response.
These are practical as they can get keeping it generic and not touching upon SRE side of things :) Every database comes it its own partitioning and sharding strategy and we need to go through their documentation to apply it. I talked about using a database proxy to bifurcate the request in one of the earlier videos, in case you are looking for that. Would recommend you picking a database and seeing how you can actually create shards and manage them. ElasticSearch can be a great start.
Hi Arpit... You have nice videos. I like interviewes with people involved in growing high scale systems. However in this video, concept explained is wrong. Partition & Shards are same (term is used interchangeably). What you are referring as Shard is Nodes (or host container). You may want to correct the same. Hope this helps.
I was literally consfused in gaining the clarity untill you came to the point where you transposed this theory into understanding through tables and the reference with SQL queries, thanks a lot to your efforts for this loving beautiful explaination Arpit sir
Excellent video Arpit . Coming from no software and system engineering background , this was the best video to explain data sharding and partioning . I am a Tech PM for AWS Supply Chain and data partitioning and sharding is real deal for us. Thank for making this extremely easy to understand video
Wow...really nice. Nowadays a lot of people are selling and talking about system design and always try to build some optimistic solution straight forward without going into the internals and in fact they have not even worked on a lot of systems. I strongly feel the way of your explanation is very very nice and I am going to buy your system design plan to improve mine.
Thanks. Looking forward to having you enrolled 🙌
2 Important points which i felt could be discussed more are 1) When you said the choice of partitioning depends on the load , usecase and access patterns , can you please give an example of each case ?? 2) When you were talking about the advantages and disadvantages of sharding , have you written these points considering only sharding and no partitioning or have you written considering both sharding and partitioning ??
Thanks!
I am just stunned how you describe every concept that easily and even if the concept is so complicated. I love you and your works man please continue doing it. I promise I will join as a member to this channel as soon as I become an earning developer. :D
Just started the Arpit videos, And Now I loved the most all over the youtube videos
Thanks Arpit for making this kind of videos
Wonderfully explained! Cleared all my doubts. Please keep making such videos. These are also well timed, not too short nor too long.
Amazing video to break down the concept for anyone! Loved it!
This is excellent, high-quality content! I always had questions about sharding and partitioning, but now I understand: sharding pertains to the database server level, while partitioning is about organizing the data itself.
You have a brilliant way to explain, only one who has gone through the journey would be able to teach it this way.
I have just started learning System Design and not from a backend background. Still able to understand the concepts. Thanks for creating such content.
One of the best videos explaining the nuances between partitioning and sharding. Thank you @ArpitBhayani
Thanks a lot ! That was well explained with clear and concise explanation. Looking forward to enrolling in your complete system design course.
I looove this kind of explanation. i.e stepping back and discussing the scenarios behind why something came up to be. Thanks a lot for these videos man!
Amazing explanation! The diagrams were really helpful in helping me solidify my understanding of the difference between sharding and partitioning.
Very good explanation with right examples. Hats off to you. Thanks for great content. I always thought shard and partitions are same but you clarified it very well.
what an explanation!!! Kudos to you! Keep enlgightning us with the knowledge.
One video and all the clutter on Sharding and Partitioning is clear. Thank you so much Arpit.
This is such a great and simple explanation of partitioning and sharding of a database. Would love to watch the video on partitioning strategies when it is uploaded.
When i finished watching this video , concepts looked super easy. Thanks
Excellent video ❤. Finally, I got a good grasp of the whole concept.
One of the best explanations on the internet, well done sir
Very beautifully and simply explained. The content of the video flowed so smoothly. Thank You @ArpitBhayani
The knowledge of amount in this video is tremendous!!! Extremely helpful 👍👍👍 thankyou sir!!
Bro your diagram example made my day. Such a clear and concise explanation of this topic. Bro dil se love u ❤❤ for making this video.
All Software Performance Enthusiats 😊,Please do also watch our Playlist on Software Performance concepts !
Great clarity and in depth explanation. Thank you
Best explanation so far. thanks brother
Very approachable - thank you!
Great explanation bro. Full clarity.
Excellent explanation.
Thanks a lot Arpit for explaining in so simplistic way. One request can you please make video on Sharding strategies and also on how composite indexes stores in the disk.
Soon.
@asli engineering - Bhai, any update on the sharding strategies.
Also, one more request is examples of scenarios to explain shard key selection.
How is the data replicated behind the scenes n stuff please ?
Nice explaination, arpit.
Awesome content Arpit ! Thanks a lot and please do continue post more on concepts such as well as analysis of real use cases.
This is really great video. Subscribed, and exploring other videos uploaded by you.
Amazing Explanation!
Partitioning can be done at table as well. So let's consider we have a table named X and it is having huge data so if we want to increase the performance and improve the latency we can partition the table into Y shards.
Wow this was really really helpful! Thank you posting this.✨
Bhai bhot videos dekhe.. this one was lit 🔥
Thanks!
Mind Blowing ❤
liked the way concepts are explained like a story.
A very clear and detailed explanation. ♥️
thank you. I always assumed that they are the same thing. This cleared things up for me.
Thanks for these practical examples and overall explanation
thanks a lot arpit sir really enjoyed and got full clarity
Very clear explanation, thanks!
Excellent ❤
Awesome Arpit, Thanks truly admire your way of teaching
Very clear explaination
Wow great explanation
Great video ! Nicely explained. :)
But I have one query , towards the end of the video :
The example you shared for "Sharding NO and partitioning YES" about Airline Check-in System and Ticket Booking System. How is that classified as partitioning if the databases are altogether different ?
Any thoughts ?
literally one of the based video i have ever seen on this topic.
Great explanation, as always. Please post a link If you have recorded any video on Partitioning strategies
When we say Shard1 or Shard2, do we mean the sql server hosted on the EC2 instance combinedly as a shard?
bohot badhia bhai .. lajawwab
Its very practical explanation...cool one
Clear explanation
Thanks so much Arpit!!
finally I understand what sharding is, thanks a ton
Such a clean explanation🙌
Great explanation!
amazing explanations, thank you
GOD of explanation !
thanks a lot arpit for an awesome explanation as always
Thanks for the explanation
this is an amazing video and your explainations are very clear
Very Nice Video, I just loved the explanation.
Simple and to the point explanation .. Thanks Arpit, Liked & Subscribed :)
well explained, thank you
Great video as always! 👍 I’ve got a question: 🤨 I have these words 🤨. (behave today finger ski upon boy assault summer exhaust beauty stereo over). What should I do with this? 🤷♂️
thank you so much , clearly understood!!
Kudos to you❤
@arpit Thanks for such dense information in so short and simple video.
However I have a query on a corner case
- How can have replicas when one has multiple shards with partitioning?
- In this case is replication locally on the shard or it can also be replicated on other shards for high availability across avalability zone or DR (like kafka architecture)?
Greatly explained
One question, at 21.00 the matrix shows what it looks like when we have both sharding and partioning, how that is different from having two databases on two different EC2 instance for two applications?
Thanks a lot u clearing confusion of long period
super video Arpit
very helpful, thanks
Dude this was amazing
Thanks, really detailed
As my view Partition is more complex because you have to work with partition key! With wrong query accidentally query scan all partition’s.
Hello arpit, at 5:49, why you mentioned that the new resources are being allocated to the EC2 machine? I think that should be allocated to the DB server running on EC2 machine right?
I meant the server running the database. The database is eventually running on some VM.
@@AsliEngineering thanks arpit
As usual amazing
Great explainer. - thanks!
Simple and efficient explanation 👍🏻
Great content, as always! I need some advice: My OKX wallet holds some USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). How can I transfer them to Binance?
Hey great video Ankit! I was wondering how sorting and specially filtering would work across shards?
Or is that an anti pattern ( just like cross shard joins )
@arpit what's the benefit of partitioning the data but not sharding it. Can you give me a usecase please?
Partitioning allows your database to read/access/move the required subset of data easily and efficiently.
1. Imagine if you partition data by time and create one partition for every hour and someone queries how many events happened in the last 10 hours, you would just need to access last 10 partition to fulfil this query. Others are not even required to be read.
2. In a distributed setup, instead of moving individual rows/elements we can easily and efficiently move partitions across the cluster for balancing the load.
Understood! Thanks 🙏
how's it decided which shard is hit by request? Is there any router in front ensuring routing of requests?
I have a doubt sir. I think increase in overall storage capacity and higher availability, doesn't got hand in hand.
If we shard and partition data, then the capacity will be available but then the data is not same in both shards i.e., if one shard becomes offline then the other shard cannot provide data if the requested data is in the offline shard. So no higher availability.
And if we only do sharding then the same data will be in both servers, and as u said if we assume 100tb, then the other will also have 100tb only? We cant get 200tb.
This is what I thought. Correct me if im wrong.
I too got the same doubt, I came to know that in this case, our system will be available but the data might be inconsistent, so still the server accepts requests and provides an empty response.
Start from 2:50
This is amazing !
When running two databases on the same machine, are we not still sharing the same underlying resources such as CPU, memory, and disk I/O?
How can u run two sql daemon on the same machine?
how do we know which partition or shard our data is located when we make query? any detailed explantion
Amazing !!
Do we use sharding when we have better options available like Oracle RAC where database can be scaled horizontally
informative without any bullshit, thanks!!
Awesome, can you give some practical examples.
These are practical as they can get keeping it generic and not touching upon SRE side of things :) Every database comes it its own partitioning and sharding strategy and we need to go through their documentation to apply it.
I talked about using a database proxy to bifurcate the request in one of the earlier videos, in case you are looking for that.
Would recommend you picking a database and seeing how you can actually create shards and manage them. ElasticSearch can be a great start.
Hi Arpit... You have nice videos. I like interviewes with people involved in growing high scale systems.
However in this video, concept explained is wrong. Partition & Shards are same (term is used interchangeably). What you are referring as Shard is Nodes (or host container). You may want to correct the same. Hope this helps.
I agree the terms are used interchangeably; but overall what i explained is correct also I cleared the same in the video as well.
Nicely expalined. :)